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公开(公告)号:ES1240654Y
公开(公告)日:2020-07-29
申请号:ES201932080
申请日:2019-12-18
Applicant: REBY INC
Inventor: GOMEZ TORRES JOSEP
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公开(公告)号:ES1240654U
公开(公告)日:2020-02-05
申请号:ES201932080
申请日:2019-12-18
Applicant: REBY INC
Inventor: GOMEZ TORRES JOSEP
Abstract: 1. Sistema para la captación de datos de contaminación atmosférica, que comprende un patinete (1) eléctrico que comprende: - un sensor de contaminación (11) configurado para detectar y/o medir, al menos, un contaminante atmosférico; y - una unidad de control (12) conectada con el sensor de contaminación (11) y configurada para recibir y almacenar y/o procesar unos datos de la contaminación atmosférica relacionada con la detección y/o medida hechas por el sensor de contaminación (11).
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公开(公告)号:US20240051390A1
公开(公告)日:2024-02-15
申请号:US17819314
申请日:2022-08-12
Applicant: Reby Inc.
Inventor: Akash Kadechkar , Elisabet Bayo Puxan , Julio Gonzalez Lopez , Xiaolei Song , Ricard Comas Xanco , Eugeni Llagostera Saltor
Abstract: A system and method for detecting rider impairment based on image or audio input is implemented in a rental fleet of lightweight vehicles. The system comprises a mobile device, a backend server, and one or more lightweight vehicles. Access to fleet vehicles is controlled by the mobile application based on results of data collected about the prospective driver.
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公开(公告)号:US20230219647A1
公开(公告)日:2023-07-13
申请号:US17647389
申请日:2022-01-07
Applicant: Reby, Inc.
Inventor: Eduard Alarcon Cot , Alvaro Ferrer Rizo , Eugeni Llagostera Saltor , Guillem Pages
CPC classification number: B62J50/22 , B62J50/25 , B62K2202/00
Abstract: A method and system for displaying indications for two-wheeled vehicles is disclosed herein. The system comprises a scooter processing unit. A rider profile database is stored at a memory coupled to the scooter processing unit. A route prediction unit is configured to predict a route of the two-wheeled vehicle based on the rider profile. A scooter motion tracking unit is configured to receive a set of sensing input parameters from at least one sensor mounted aboard the two-wheeled vehicle and a Control interface (CI), and for detecting a start instance and an end instance of a manoeuvre being performed by the two-wheeled vehicle. An indication control unit, communicatively coupled to the scooter motion tracking unit, is configured to receive a trigger signal corresponding to the start instance, and an end signal corresponding to the end instance for controlling the operation of an LED indicator.
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公开(公告)号:US20240054762A1
公开(公告)日:2024-02-15
申请号:US17819312
申请日:2022-08-12
Applicant: Reby Inc.
Inventor: Julio Gonzalez Lopez , Elisabet Bayo Puxan , Akash Kadechkar , Xiaolei Song , Ricard Comas Xanco , Eugeni Llagostera Saltor
IPC: G06V10/764 , G06V10/774 , G06V10/75 , B62J11/24
CPC classification number: G06V10/764 , G06V10/774 , G06V10/759 , B62J11/24 , B62K3/002
Abstract: An image classification system and method are used to determine the status of equipment completeness of the rental two-wheeled vehicles, such as electric scooters. The system and method use deep learning models to analyze and classify ambiguous states of the rental vehicle when the user finishes the ride. These states are likely to be encountered by rental vehicles, to protect helmets, trunks or other equipment from loss or damage.
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公开(公告)号:US20240049830A1
公开(公告)日:2024-02-15
申请号:US17819313
申请日:2022-08-12
Applicant: Reby Inc.
Inventor: Ricard Comas Xanco , Elisabet Bayo Puxan , Julio Gonazalez Lopez , Akash Kadechkar , Xiaolei Song , Eugeni Llagostera Saltor
IPC: A42B3/30
CPC classification number: A42B3/30
Abstract: A smart system for detecting the presence of a helmet in a vehicle is disclosed herein. The system comprises a first transceiver configured within a trunk of the vehicle. The first transceiver is configured to transmit a first detection signal on detecting the opening of the trunk of the vehicle. At least one second transceiver corresponds to at least one helmet provided on the body of the helmet. The second transceiver is configured to respond to the first detection signal with a response signal, wherein the response signal includes a unique identity marker corresponding to the helmet. A transmission device is configured to detect opening and closing of trunk to activate the first transceiver, subsequent to which the first detection signal is sent, and the transmission device is further configured to transmit information associated with the response signal to a base controller.
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公开(公告)号:US20230222903A1
公开(公告)日:2023-07-13
申请号:US17647385
申请日:2022-01-07
Applicant: Reby Inc.
IPC: G08G1/017 , G06V10/774 , G06V10/764 , G06T7/70
CPC classification number: G08G1/0175 , G06V10/774 , G06V10/765 , G06T7/70 , G06V2201/08 , G06T2207/20081
Abstract: An image classification system and method is used to detect the parking status of lightweight vehicles, such as kick scooters. The system and method uses a deep learning model to analyze and classify ambiguous parking states that are likely to be encountered by lightweight vehicles, which are small and light enough to be parked in many different environments.
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公开(公告)号:US20240054795A1
公开(公告)日:2024-02-15
申请号:US17819311
申请日:2022-08-12
Applicant: Reby Inc.
Inventor: Elizabet Bayo Puxan , Eugeni Llagostera Saltor , Xiaolei Song , Akash Kadechkar , Ricard Comas Xanco , Julio Gonzalez Lopez
CPC classification number: G06V20/625 , G06V30/19013 , G06V30/12 , G06V30/1473 , G06V30/1444 , G06K7/1417 , G06K7/10712 , G06V2201/08
Abstract: The present disclosure relates to a system and method for automatic vehicle recognition, based on a smart device. The system mainly includes an image capturing device integrated in the smart device, a data storage to store the images captured by the image capturing device and known identity aspects related to a vehicle allotted to a user, and a License plate processing and matching (LPPM) component to perform recognition process. LPPM component includes an identity aspect detector to detect a portion representing the identity aspect, an image processor to enhance the portion and perform Optical Characters Recognition (OCR) to extract character strings from the portion. The character string is compared against a character string of the known identity aspect to verify the vehicle.
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公开(公告)号:US20240054554A1
公开(公告)日:2024-02-15
申请号:US17819316
申请日:2022-08-12
Applicant: Reby Inc.
Inventor: Ricard Comas Xanco , Elisabet Bayo Puxan , Julio Gonzalez Lopez , Akash Kadechkar , Xiaolei Song , Eugeni Llagostera Saltor
CPC classification number: G06Q30/0645 , G08B21/18 , B62J45/41
Abstract: A system and method for rider profiling for lightweight vehicles is disclosed herein. The system comprises a lightweight vehicle actuating unit. Load-cells are configured on a deck of the lightweight vehicle for sensing and measuring load acting thereupon for generating a measurement signal. A pressure-pattern collection unit receives the measurement signal to identify and process a load pattern acting on the deck to generate a pressure-pattern signal. A learning model receives the pressure-pattern signal for processing to obtain information associated with a pose of the rider. A riding control is coupled to a riding control database and configured to unit receive the information associated with the pose from the learning model for determining at least one instance of rule violation and computing a decision based on the at least one instance of rule violation.
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公开(公告)号:US20240053745A1
公开(公告)日:2024-02-15
申请号:US17819315
申请日:2022-08-12
Applicant: Reby Inc.
Inventor: Akash Kadechkar , Elisabet Bayo Puxan , Julio Gonzalez Lopez , Xiaolei Song , Richard Comas Xanco , Eugeni Llagostera Saltor
CPC classification number: G05D1/0038 , G06F1/163 , G05D1/021 , G05D1/0016 , A42B3/30
Abstract: An XR helmet collects user data and environmental data using onboard sensors. The collected data is used to train a model for predicting safe rides in a rental fleet of lightweight vehicles. The XR helmet is configured to selectively take control of the lightweight vehicle when driver biofeedback or environmental data are predictive of unsafe driving conditions. Access and control of fleet vehicles is controlled by a predictive machine learning model trained by data indicative of safe and unsafe driving conditions.
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